Some of the biggest problems in medicine don't get written about, because they don't concern eye-catching things such as one patient's valiant struggle: they're protected from public scrutiny by a wall of tediousness.

Here is one problem that affects millions of people. What if we had rubbish evidence on whether hundreds of common treatments really work, simply because nobody asked the right research question? A paper published this week looks at how much evidence there was for every one of the new drugs approved by the FDA between 2000 and 2010, at the time they were approved.

You might think drugs only get on the market if they've been shown to be useful. But "useful" can mean many different things: for FDA approval, for example, you only need trials to show your drug is better than a placebo. That's nice, but with most medical problems, we've already got some kind of treatment. We're not interested in whether your drug is better than nothing. We're interested in whether it's better than the best currently available option.

So it turns out that, out of all the 197 new drugs approved in the past decade, only 70% had data to show they were better than other treatments (and that's after you ignore drugs for conditions where there was no current treatment).

But the problems go beyond just using the wrong comparator: most of the trials we rely on to make real-world decisions also study drugs on highly unrepresentative, freakishly ideal patients. These patients are younger, with perfect single diagnoses, fewer other health problems, and so on.

This can stretch to absurd extremes. Earlier this year, some researchers from Finland took every patient who'd ever had a hip fracture and worked out if they would have been eligible for the trials that have been done on fracture-preventing bisphosphonate drugs, which are in wide use.

Starting with all 7,411 fractures, 2,134 patients get excluded straight off, because they're men, and the trials have been done on women. Then, from the 5,277 remaining, 3,596 get excluded again, because they're the wrong age: patients in trials had to be between 65 and 79. Then, finally, 609 more fracture patients get excluded, because they've not got osteoporosis.

This leaves 1,072 patients. So the data from the trials on these fracture-preventing drugs are only strictly applicable to about one of every seven patients with a fracture: they might still work in those who've been excluded, though that's not a judgment call you should have to make; and one problem, in particular, is that the size of the benefit might be different in different people.

To understand why this matters, finally, we need to go through one more study (written by people I work with, though I don't know if that's transparency or a boast). The new "coxib" painkiller drugs are sold on the basis that they cause fewer gastrointestinal bleeds than cheap old painkillers such as ibuprofen: and coxibs do seem to do this.

But the trials were conducted in ideal patients, who were at much higher risk of having a GI bleed, and this causes problems when you do a cost benefit analysis. Nice (National Institute for Healthcare and Clinical Excellence) estimated the cost of preventing one bleed, if you use a coxib instead of an older drug, at $20,000. But that's a huge underestimate, and here's why: they estimated the number of avoided bleeds from the figures in the trials, where patients were at high risk of bleeds.

If, instead, you look at the real data on people prescribed coxibs, in a database of GP records, the overall number of bleeds among people getting painkillers is much smaller: so the number of bleeds avoided is also smaller, and so the cost of each avoided bleed is higher: $104,000, in fact.

This explanation might make your eyes glaze over. You assume someone else is dealing with it. And that's why problems like these don't get fixed.